Improving palm oil quality through identification and mapping of the lipase gene causing oil deterioration.

The oil palm fruit mesocarp contains high lipase activity that increases free fatty acids and necessitates post-harvest inactivation by heat treatment of fruit bunches. Even before heat treatment the mesocarp lipase activity causes consequential oil losses and requires costly measures to limit free fatty acids quantities. Here we demonstrate that elite low-lipase lines yield oil with substantially less free fatty acids than standard genotypes, allowing more flexibility for post-harvest fruit processing and extended ripening for increased yields. We identify the lipase and its gene cosegregates with the low-/high-lipase trait, providing breeders a marker to rapidly identify potent elite genitors and introgress the trait into major cultivars. Overall, economic gains brought by wide adoption of this material could represent up to one billion dollars per year. Expected benefits concern all planters but are likely to be highest for African smallholders who would be more able to produce oil that meets international quality standards.

QTL detection by multi-parent linkage mapping in oil palm (Elaeis guineensis Jacq.).

A quantitative trait locus (QTL) analysis designed for a multi-parent population was carried out and tested in oil palm (Elaeis guineensis Jacq.), which is a diploid cross-fertilising perennial species. A new extension of the MCQTL package was especially designed for crosses between heterozygous parents. The algorithm, which is now available for any allogamous species, was used to perform and compare two types of QTL search for small size families, within-family analysis and across-family analysis, using data from a 2 x 2 complete factorial mating experiment involving four parents from three selected gene pools. A consensus genetic map of the factorial design was produced using 251 microsatellite loci, the locus of the Sh major gene controlling fruit shell presence, and an AFLP marker of that gene. A set of 76 QTLs involved in 24 quantitative phenotypic traits was identified. A comparison of the QTL detection results showed that the across-family analysis proved to be efficient due to the interconnected families, but the family size issue is just partially solved. The identification of QTL markers for small progeny numbers and for marker-assisted selection strategies is discussed.